MESOSCALE APPLICATIONS

Anderson, C. J., R. W. Arritt, J. S. Kain, 2007: An alternative mass flux profile in the Kain-Fritsch convective parameterization and its effect on seasonal precipitation.. J. Hydrometeor, 8, 1128-1140.

Baldwin, M. E., S. Lakshmivarahan, J. S. Kain, 2005: Development of an automated classification procedure for rainfall systems. Monthly Weather Review, 133, 844-862.

Baldwin, M. E., K. L. Elmore, 2005: Objective verification of high-resolution WRF forecasts during 2005 NSSL/SPC Spring Program. Preprints, 21st Conference on Weather Analysis and Forecasting/17th Conference on Numerical Weather Prediction., Durham, NC, USA, American Meteorologocal Society, 11B.4. [Available from Michael Baldwin, 1313 Halley Circle, Norman, OK, USA, 73069.]

Forecast output from several versions of the WRF model will be evaluated during the 2005 NSSL/SPC Spring Program. These include a ~4km grid-spacing version of the WRF-NMM run at NCEP, a ~4km version of WRF-ARW run at NCAR, and a ~2km version of WRF-ARW run by CAPS at PSC. This output will be evaluated subjectively in real-time by teams of operational forecasters and researchers (see Kain et al. 2005, 21st WAF/17th NWP conf). In addition, several objective verification techniques will be applied to these forecasts, in particular, predicted and observed composite radar reflectivities will be compared. Object-oriented techniques will be used to compare the forecast and observed characteristics of a variety of rainfall systems. Other statistical techniques will be applied in order to measure biases in the forecast fields, structure, etc. This paper will report on ongoing research related to meaningful, objective verification of forecasts that contain realistic, high-resolution detail.

Baldwin, M. E., J. S. Kain, 2006: Sensitivity of Several Performance Measures to Displacement Error, Bias, and Event Frequency. Weather and Forecasting, 21, 636-648.

The sensitivity of various accuracy measures to displacement error, bias, and event frequency is analyzed for a simple hypothetical forecasting situation. Each measure is found to be sensitive to displacement error and bias, but probability of detection and threat score do not change as a function of event frequency. On the other hand, equitable threat score, true skill statistic, and odds ratio skill score behave differently with changing event frequency. A newly devised measure, here called the bias-adjusted threat score, does not change with varying event frequency and is reletively insensitive to bias. Numerous plots are presented to allow users of these accuracy measures to make quantitative estimates of sensitivities that are relevant to their particular application.

Available online at ://http://available soon from AMS.

Banacos, P. C., D. M. Schultz, 2005: The use of moisture flux convergence in forecasting convective initiation: Historical and operational perspectives. Weather and Forecasting, 20, 351-366.

Moisture flux convergence (MFC) is a term in the conservation of water vapor equation and was first calculated in the 1950s and 1960s as a vertically integrated quantity to predict rainfall associated with synoptic-scale systems. Vertically integrated MFC was also incorporated into the Kuo cumulus parameterization scheme for the Tropics. MFC was eventually suggested for use in forecasting convective initiation in the midlatitudes in 1970, but practical MFC usage quickly evolved to include only surface data, owing to the higher spatial and temporal resolution of surface observations. Since then, surface MFC has been widely applied as a short-term (0-3 h) prognostic quantity for forecasting convective initiation, with an emphasis on determining the favorable spatial location(s) for such development. A scale analysis shows that surface MFC is directly proportional to the horizontal mass convergence field, allowing MFC to be highly effective in highlighting mesoscale boundaries between different air masses near the earth's surface that can be resolved by surface data and appropriate grid spacing in gridded analyses and numerical models. However, the effectiveness of boundaries in generating deep moist convection is influenced by many factors, including the depth of the vertical circulation along the boundary and the presence of convective available potential energy (CAPE) and convective inhibition (CIN) near the boundary. Moreover, lower- and upper-tropospheric jets, frontogenesis, and other forcing mechanisms may produce horizontal mass convergence above the surface, providing the necessary lift to bring elevated parcels to their level of free convection without connection to the boundary layer. Case examples elucidate these points as a context for applying horizontal mass convergence for convective initiation. Because horizontal mass convergence is a more appropriate diagnostic in an ingredients-based methodology for forecasting convective initiation, its use is recommended over MFC.

Barnes, L. R., E. C. Gruntfest, M. H. Hayden, D. M. Schultz, C. Benight, 2007: False alarms and close calls: A conceptual model of warning accuracy. Weather and Forecasting, 22, 1140-1147.

Brooks, H. E., 2006: A global view of severe thunderstorms: Estimating the current distribution and possible future changes. Preprints, Symposium on the Challenges of Severe Convective Storms, Atlanta, GA, USA, American Meteorological Society, CD-ROM, J4.2.

Brooks, H. E., A. R. Anderson, K. Riemann, I. Ebbers, H. Flachs, 2007: Climatological aspects of convective parameters from the NCAR/NCEP reanalysis. Atmospheric Research, 83, 294-305.

Annual cycles of convectively important atmospheric parameters have been computed for a variety of from the National Center for Atmospheric Research (NCAR)/National Centers for Environmental Prediction (NCEP) global reanalysis, using 7 years of reanalysis data. Regions in the central United States show stronger seasonality in combinations of thermodynamic parameters than found elsewhere in North America or Europe. As a result, there is a period of time in spring and early summer when climatological mean conditions are supportive of severe thunderstorms.
The annual cycles help in understanding the large-scale processes that lead to the combination of atmospheric ingredients necessary for strong convection. This, in turn, lays groundwork for possible changes in distribution of the environments associated with possible global climate change.

Available online at ://http://www.nssl.noaa.gov/users/brooks/public_html/papers/ECSS2004.pdf.

Brooks, H. E., 2007: Development and use of climatologies of convective weather. Atmospheic Convection: Research and Operational Forecasting Aspects, D. B. Gaiotti, R. Steinacker, F. Stel, Ed(s)., SpringerWienNew York, 123-132.

Estimates of the occurrence (“climatologies”) of convective phenomena in time, space, and intensity can be useful in a variety of contexts. They provide background for forecasters, and the risk management and meteorological research communities. In part, because of the different needs of those user groups, caution must be applied when developing and using climatologies, especially if the intended application is outside of the original intent of the developers.

Brooks, H. E., 2007: Environmental conditions associated with convective phenomena: Proximity soundings. Atmospheic Convection: Research and Operational Forecasting Aspects, D. B. Gaiotti, R. Steinacker, F. Stel, Ed(s)., SpringerWeinNewYork, 113-122.

An important tool in understanding the relationship between environments and observed severe thunderstorm events are vertical profiles of environmental conditions collected in the vicinity of the storms. These relationships can help in the future forecasting of weather. In this paper, the use and cautions associated with these so-called proximity soundings are discussed.

Brooks, H. E., 2007: Ingredients-based forecasting. Atmospheic Convection: Research and Operational Forecasting Aspects, D. B. Gaiotti, R. Steinacker, Ed(s)., SpringerWienNew York, 133-140.

Forecasting the weather can be thought of as a problem in extracting a small signal from a noisy background field. Much information is available to the forecaster, but, frequently, only a small amount of that information is of importance for solving the forecast problem(s) of the day. As a result, an approach to forecasting must maximize the efficiency of the process. An effective way, particularly for hazardous weather, is to identify the ingredients required to produce a particular weather event and then to focus on the processes that can affect the presence of those ingredients. This allows the forecaster to narrow the range of aspects of the observations and model guidance that are considered during the forecast shift and, it is hoped, identify crucial developments as they occur.

Brooks, H. E., 2007: Practical Aspects of Forecasting Severe Convection in the United States: Environmental Conditions and Initiation. Atmospheic Convection: Research and Operational Forecasting Aspects, D. B. Gaiotti, R. Steinacker, F. Stel, Ed(s)., SpringerWienNew York, 141-148.

The first stage of forecasting convective weather involves forecasting the evolution of conditions that are favorable for the development of storms and their probable initiation. The scale of the forecasts are typically on the order of 100 km or larger and the lead time between the forecast and storms is 1-48 hours. In the United States, procedures have evolved so that the Storm Prediction Center of the National Weather Service has the responsibility for issuing these forecasts for the contiguous 48 states (the part of the US excluding Alaska and Hawaii.)

Brooks, H. E., 2007: Practical Aspects of Forecasting Severe Convection in the United States: Storm Evolution and Warning. Atmospheic Convection: Research and Operational Forecasting Aspects, D. B. Gaiotti, R. Steinacker, F. Stel, Ed(s)., SpringerWienNew York, 149-156.

In order to protect life and property, forecasts of severe convection are critical on short time and space scales (on the order of 1 hour or less and a few 10s of km or less). Accurate assessment of the environment and monitoring of high-resolution observational data, frequently focusing on radar-observed evolution, are essential in this process. In the United States, these short-term time and space scale forecasts are referred to as warnings and are prepared by local forecast offices of the National Weather Service, who have responsibility for forecasters on the order of 100,000 km2.

Brooks, H. E., C. A. Doswell III, D. Sutter, 2008: Low-Level Winds in Tornadoes and Potential Catastrophic Tornado Impacts in Urban Areas. Bulletin of the American Meteorological Society, 89, 87-90.

Brooks, H. E., N. Dotzek, 2008: The spatial distribution of severe convective storms and an analysis of their secular changes. Climate Extremes and Society, H. F. Diaz, Ed(s)., Cambridge University Press, 35-54.

Severe convective storms are responsible for billions of US dollars in damage each year around the world. They form an important part of the climate system by redistributing heat, moisture, and trace gases, as well as producing large quantities of precipitation.

Reporting of severe convection varies from country to country, however, so that determining their distribution from the reports alone is difficult, at best. Evidence does exist that the intensity of some events, particularly tornadoes, follows similar distributions in different locations, making it possible to build statistical models of occurrence. Remotely-sensed observations provide some insight, but the relationship between the observable parameters and the actual events of interest limits the quality of the estimate. Another approach is to use observations of the larger-scale environments.

As has been stated, the relationship between the observation and the event limits the estimate, but global coverage is possible. Time series of the favorable environments can also be developed from such data. In order to improve the estimates, the most pressing need is better observational data of events. Very few countries have formal systems for collection of severe thunderstorm reports. A new effort from a consortium of researchers in Europe to develop a continental-wide database offers the possibility of a significant improvement in data in that part of the world.

Brown, R. A., B. A. Flickinger, E. Forren, D. M. Schultz, D. Sirmans, P. L. Spencer, V. T. Wood, C. L. Ziegler, 2005: Improved detection of severe storms using experimental fine-resolution WSR-88D measurements. Weather and Forecasting, 20, 3-14.

Doppler velocity and reflectivity measurements from WSR-88D (Weather Surveillance Radar - 1988 Doppler) radars provide important input to forecasters as they prepare to issue short-term severe storm and tornado warnings. Current-resolution data collected by the radars have an azimuthal spacing of 1.0° and range spacing of 1.0 km for reflectivity and 0.25 km for Doppler velocity and spectrum width. To test the feasibility of improving data resolution, National Severe Storms Laboratory's test-bed WSR-88D (KOUN) collected data in severe thunderstorms using 0.5° azimuthal spacing and 0.25 km range spacing,resulting in eight times the resolution for reflectivity and twice the resolution for Doppler velocity and spectrum width. Displays of current-resolution WSR-88D Doppler velocity and reflectivity signatures in severe storms were compared with displays showing finer-resolution signatures. At all ranges, fine-resolution data provided better depiction of severe storm characteristics. Eighty-five percent of mean rotational velocities derived from fine-resolution mesocyclone signatures were stronger than velocities derived from current-resolution signatures. Likewise, about 85% of Doppler velocity differences across tornado and tornadic vortex signatures were stronger than values derived from current-resolution data. In addition, low-altitude boundaries were more readily detected using fine-resolution reflectivity data. At ranges greater than 100 km, fine-resolution reflectivity displays revealed severe storm signatures, such as bounded weak echo regions and hook echoes, which were not readily apparent on current-resolution displays. Thus, the primary advantage of fine-resolution measurements over current-resolution measurements is the ability to detect stronger reflectivity and Doppler velocity signatures at greater ranges from a WSR-88D.

Bukovsky, M. S., J. S. Kain, M. E. Baldwin, 2005: Bowing convective systems in a popular operational model: Are they for real. Preprints, 21st Conference on Weather Analysis and Forecasting/17th Conference on Numerical Weather Prediction, Washington, DC, USA, American Meteorological Society, 2A.1.

Bukovsky, M. S., J. S. Kain, M. E. Baldwin, 2006: Bowing Convective Systems in a Popular Operational Model: Are They for Real?. Weather and Forecasting, 21, 307-324.

Bowing, propagating precipitation features that sometimes appear in NCEP's North American Mesoscale model (NAM; formerly called the Eta Model) forecasts are examined. These features are shown to be associated with an unusual convective heating profile generated by the Betts–Miller–Janji convective parameterization in certain environments. A key component of this profile is a deep layer of cooling in the lower to middle troposphere. This strong cooling tendency induces circulations that favor expansion of parameterized convective activity into nearby grid columns, which can lead to growing, self-perpetuating mesoscale systems under certain conditions. The propagation characteristics of these systems are examined and three contributing mechanisms of propagation are identified. These include a mesoscale downdraft induced by the deep lower-to-middle tropospheric cooling, a convectively induced buoyancy bore, and a boundary layer cold pool that is indirectly produced by the convective scheme in this environment. Each of these mechanisms destabilizes the adjacent atmosphere and decreases convective inhibition in nearby grid columns, promoting new convective development, expansion, and propagation of the larger system. These systems appear to show a poor correspondence with observations of bow echoes on time and space scales that are relevant for regional weather prediction, but they may provide important clues about the propagation mechanisms of real convective systems.

Cohen, R. A., D. M. Schultz, 2005: Contraction rate and its relationship to frontogenesis, the Lyapunov exponent, fluid trapping, and airstream boundaries. Monthly Weather Review, 133, 1353-1369.

Cohen, R. A., D. M. Schultz, 2006: Reply. Monthly Weather Review, 134, 2644-2644.

Coniglio, M. C., H. E. Brooks, S. J. Weiss, 2005: Use of proximity sounding parameters to improve the prediction of MCS speed and demise. 21st Conference on Weather Analysis and Forecasting, Washington, DC, USA, American Meteorological Society, 3.3.

Coniglio, M. C., H. E. Brooks, S. F. Corfidi, S. J. Weiss, 2007: Forecasting the Maintenance of Quasi-Linear Mesoscale Convective Systems. Weather and Forecasting, 22, 556-570.

The problem of forecasting the maintenance of mesoscale convective systems (MCSs) is investigated through an examination of observed proximity soundings. Furthermore, environmental variables that are statistically different between mature and weakening MCSs are input into a logistic regression procedure to develop probabilistic guidance on MCS maintenance, focusing on warm-season quasi-linear systems that persist for several hours.
Between the mature and weakening MCSs, shear vector magnitudes over very deep layers are the best discriminators among hundreds of kinematic and thermodynamic variables. An analysis of the shear profiles reveals that the shear component perpendicular to MCS motion (usually parallel to the leading line) accounts for much of this difference in low levels and the shear component parallel to MCS motion accounts for much of this difference in mid-to-upper levels. The lapse rates over a significant portion of the convective cloud layer, the convective available potential energy, and the deep-layer mean wind speed are also very good discriminators and collectively provide a high level of discrimination between the mature and dissipation soundings as revealed by linear discriminant analysis. Probabilistic equations developed from these variables used with short-term numerical model output show utility in forecasting the transition of an MCS with a solid line of 50+ dbZ echoes to a more disorganized system with unsteady changes in structure and propagation. This study shows that empirical forecast tools based on environmental relationships still have the potential to provide forecasters with improved information on the qualitative characteristics of MCS structure and longevity. This is especially important since the current and near-term value added by explicit numerical forecasts of convection is still uncertain.

Coniglio, M. C., J. S. Kain, S. J. Weiss, M. Xue, M. L. Weisman, Z. I. Janjic, 2007: Evaluating storm-scale model output for severe-weather forecasting: The 2007 NOAA HWT Spring Experiment.. Preprints, 4th European Conference on Severe Storms, Trieste, Italy, International Centre for Theoretical Physics, CD-ROM, 03.11.

Corfidi, S. F., S. J. Corfidi, D. M. Schultz, 2006: Toward a better understanding of elevated convection. Preprints, 23rd Conf. on Severe Local Storms, St. Louis, MO, USA, Amer. Meteor. Soc., CD-ROM, P1.5.

Available online at ://http://ams.confex.com/ams/23SLS/techprogram/paper_115485.htm.

Doswell, C. A., D. M. Schultz, 2006: On the use of indices and parameters in forecasting severe storms. Electronic Journal of Severe Storms Meteorology, 1(3), 1-22.

This paper discusses our concept of the proper (and improper) use of diagnostic variables in severe-storm forecasting. A framework for classification of diagnostic variables is developed, indicating the limi-tations of such variables and their suitability for operational diagnosis and forecasting. The utility of diag-nostic indices and parameters as prognostic tools for forecasting is discussed, revealing the relevant issues in designing new diagnostic variables used for making weather forecasts. Finally, criteria required to claim that a new diagnostic variable represents an effective prognostic variable are proposed. We argue that few, if any, diagnostic variables have met these criteria for demonstrated utility at prognosis.

Available online at ://http://www.ejssm.org/ojs/index.php/ejssm/issue/view/3.

Doswell III, C. A., H. E. Brooks, M. P. Kay, 2005: Climatological estimates of daily local nontornadic severe thunderstorm probability for the United States. Weather and Forecasting, 20, 577-595.

The probability of nontornadic severe weather event reports near any location in the United States for any day of the year has been estimated. Gaussian smoothers in space and time have been applied to the observed record of severe thunderstorm occurrence from 1980 to 1994 to produce daily maps and annual cycles at any point. Many aspects of this climatology have been identified in previous work, but the method allows for the consideration of the record in several new ways. A review of the raw data, broken down in various ways, reveals that numerous nonmeteorological artifacts are present in the raw data. These are predominantly associated with the marginal nontornadic severe thunderstorm events, including an enormous growth in the number of severe weather reports since the mid-1950s. Much of this growth may be associated with a drive to improve warning verification scores. The smoothed spatial and temporal distributions of the probability of nontornadic severe thunderstorm events are presented in several ways. The distribution of significant nontornadic severe thunderstorm reports (wind speeds 65 kt and/or hailstone diameters 2 in.) is consistent with the hypothesis that supercells are responsible for the majority of such reports.

Douglas, M., J. M. Galvez, J. F. Mejia, C. Brown, R. Orozco, C. Watts, 2005: Seasonal evolution of the sea-land breeze circulation and its role in the precipitation climatology of northwestern Mexico. Preprints, 6th Conference on Coastal Atmospheric and Oceanic Prediction and Processes (6COASTAL), San Diego, CA, USA, American Meteorological Society, CD-ROM, 3.7.

Douglas, M. W., J. Mejia, J. Murillo, R. Orozco, 2007: Spatial Structure of Cloudiness Associated with the Mid-Summer Drought from MODIS and GOES Imagery. Extended Abstracts, AGU Joint Assembly, Acapulco, Mexico, AGU, H51G-04.

Elmore, K. L., M. E. Baldwin, D. M. Schultz, 2006: Field Significance Revisited: Spatial Bias Errors in Forecasts as Applied to the Eta Model. Monthly Weather Review, 134, 519-531.

The spatial structure of bias errors in numerical model output is valuable to both model developers and operational forecasters, especially if the field containing the structure itself has statistical significance in the face of naturally occurring spatial correlation. A semi-parametric
Monte Carlo method, along with a moving blocks bootstrap method is used to determine the field significance of spatial bias errors within spatially correlated error fields. This process can be completely automated, making it an attractive addition to the verification tools already in use. The process demonstrated here results in statistically significant spatial bias error fields at any arbitrary
significance level.

To demonstrate the technique, 0000 and 1200 UTC runs of the operational Eta model and the operational Eta model using the Kain–Fritsch convective parameterization scheme are examined. The resulting fields for forecast errors for geopotential heights and winds at 850, 700, 500, and 250 hPa over a period of 14 months (26 January 2001 through 31 March 2002) are examined and compared using the verifying initial analysis. Specific examples are shown, and some plausible causes for the resulting significant bias errors are proposed.

Elmore, K. L., D. M. Schultz, M. E. Baldwin, 2006: The Behavior of Synoptic-Scale Errors in the Eta Model. Monthly Weather Review, 134, 3355-3366.

A previous study of the mean spatial bias errors associated with operational forecast models motivated an examination of the mechanisms responsible for these biases. One hypothesis for the cause of these errors is that mobile synoptic-scale phenomena are partially responsible. This paper explores this hypothesis using 24-h forecasts from the operational Eta model and an experimental version called the EtaKF.
For a sample of 44 well-defined upper-level short-wave troughs arriving on the west coast of the United States, 70% were underforecast (as measured by the 500-hPa geopotential height), a likely result of being undersampled by the observational network. For a different sample of 45 troughs that could be tracked easily across the country, consecutive model runs showed that the height errors associated with 44% of the troughs generally decreased in time, 11% increased in time, 18% had relatively steady errors, 2% were uninitialized entering the west coast, and 24% exhibited some other kind of behavior. Thus, landfalling short-wave troughs were typically underforecast (positive errors, heights too high), but these errors tended to decrease as they moved across the United States, likely a result of being better initialized as the troughs became influenced by more upper-air data. Nevertheless, some errors in short-wave troughs were not corrected as they fell under the influence of supposedly increased data amount and quality. These results indirectly show the effect that the amount and quality of observational data has on the synoptic-scale errors in the models. On the other hand, long-wave ridges tended to be underforecast (negative errors, heights too low) over a much larger horizontal extent.
These results are confirmed in a more systematic manner over the entire dataset by segregating the model output at each grid point by the sign of the 500-hPa relative vorticity. Although errors at grid points with positive relative vorticity are small but positive in the western United States, the errors become large and negative farther east. Errors at grid points with negative relative vorticity, on the other hand, are generally negative across the United States. A large negative bias observed in the Eta and EtaKF over the southeast United States is believed to be due to an error in the longwave radiation scheme interacting with water vapor and clouds. This study shows that model errors may be related to the synoptic-scale flow, and even large scale features such as long-wave troughs can be associated with significant large-scale height errors.

Available online at ://http://ams.allenpress.com/.

Gallus, W. A., M. E. Baldwin, K. L. Elmore, 2007: Evaluation of probabilistic precipitation forecasts determined from Eta and AVN forecasted amounts.. Weather and Forecasting, 22, 207-215.

This note examines the connection between the probability of precipitation and forecasted amounts from the NCEP Eta (now known as the North American Mesoscale model) and Aviation (AVN; now known as the Global Forecast System) models run over a 2-yr period on a contiguous U.S. domain. Specifically, the quantitative precipitation forecast (QPF)–probability relationship found recently by Gallus and Segal in 10-km grid spacing model runs for 20 warm season mesoscale convective systems is tested over this much larger temporal and spatial dataset. A 1-yr period was used to investigate the QPF–probability relationship, and the predictive capability of this relationship was then tested on an independent 1-yr sample of data. The same relationship of a substantial increase in the likelihood of observed rainfall exceeding a specified threshold in areas where model runs forecasted higher rainfall amounts is found to hold over all seasons. Rainfall is less likely to occur in those areas where the models indicate none than it is elsewhere in the domain; it is more likely to occur in those regions where rainfall is predicted, especially where the predicted rainfall amounts are largest. The probability of rainfall forecasts based on this relationship are found to possess skill as measured by relative operating characteristic curves, reliability diagrams, and Brier skill scores. Skillful forecasts from the technique exist throughout the 48-h periods for which Eta and AVN output were available. The results suggest that this forecasting tool might assist forecasters throughout the year in a wide variety of weather events and not only in areas of difficult-to-forecast convective systems.

Gilleland, E., M. Pocernich, H. E. Brooks, 2006: Analyzing the Extreme Behavior of Large-Scale Meteorlogical Variables Found To Have Influence on Severe Storms and Tornadic Events Using Global Reanalysis Data. Extended Abstracts, 2006 Joint Statistical Meetings (JSM) of the American Statistical Association (ASA): Statistics for an uncertain world: Meeting global challenges, Seattle, WA, USA, American Statistical Association, 453-453.

Gochis, D., D. M. Schultz, . et al., 2005: The Water Cycle Across Scales. Bulletin of the American Meteorological Society, 86, 1743-1746.

Gutowski, Jr., W. J., G. C. Hegerl, G. J. Holland, T. R. Knutson, L. O. Mearns, R. J. Stouffer, P. J. Webster, M. F. Wehner, F. W. Zwiers, H. E. Brooks, K. A. Emanuel, P. D. Komar, J. P. Kossin, K. E. Kunkel, R. McDonald, G. A. Meehl, R. J. Trapp, 2008: Causes of Observed Changes in Extremes and Projections of Future Changes. Weather and Climate Extremes in a Changing Climate Regions of Focus: North America, Hawaii, Caribbean, and U.S. Pacific Islands: Synthesis and Assessment Product 3.3 Report by the U.S. Climate Change Science Program and the Subcommittee on Global Change, T. R. Karl, G. A. Meehl, C. D. Miller, S. J. Hassol, A. M. Waple, W. L. Murray, Ed(s)., U.S. Climate Change Science Program and the Subcommittee on Glob, 81-116.

Hamill, T. M., R. Schneider, H. E. Brooks, G. Forbes, H. B. Bluestein, M. Steinberg, D. Melendez, R. M. Dole, 2005: The May 2003 extended tornado outbreak. Bulletin of the American Meteorological Society, 86, 531-542.

In May 2003 there was a very destructive extended outbreak of tornadoes across the central and eastern United States. More than a dozen tornadoes struck each day from 3 May to 11 May 2003. This outbreak caused 41 fatalities, 642 injuries, and approximately $829 million dollars of property damage. The outbreak set a record for most tornadoes ever reported in a week (334 between 4-10 May), and strong tornadoes (F2 or greater) occurred in an unbroken sequence of nine straight days. Fortunately, despite this being one of the largest extended outbreaks of tornadoes on record, it did not cause as many fatalities as in the few comparable past outbreaks, due in large measure to the warning efforts of National Weather Service, television, and private-company forecasters and the smaller number of violent (F4-F5) tornadoes. This event was also relatively predictable; the onset of the outbreak was forecast skillfully many days in advance.

An unusually persistent upper-level trough in the intermountain west and sustained low-level southerly winds through the southern Great Plains produced the extended period of tornado-favorable conditions. Three other extended outbreaks in the past 88 years were statistically comparable to this outbreak, and two short-duration events (Palm Sunday 1965 and the 1974 Superoutbreak) were comparable in the overall number of strong tornadoes. An analysis of tornado statistics and environmental conditions indicates that extended outbreaks of this character occur roughly every 10 to 100 years.

Heinselman, P. L., D. M. Schultz, 2006: Intraseasonal variability of summertime storms over central Arizona during 1997 and 1999. Weather and Forecasting, 21, 559-578.

Although previous climatologies over central Arizona show a summer diurnal precipitation cycle, on any given day precipitation may differ dramatically from this climatology. The purpose of this study is to investigate the intraseasonal variability of diurnal storm development over Arizona and explore the relationship to the synoptic-scale flow and Phoenix soundings during the 1997 and 1999 North American Monsoons (NAMs). Radar reflectivity mosaics constructed from Phoenix and Flagstaff Weather Surveillance Radar-1988 Doppler (WSR-88D) reflectivity data reveal six repeated storm development patterns or regimes. The diurnal evolution of each regime is illustrated by computing frequency maps of reflectivity 25 dBZ and greater during 3-h periods. These regimes are named to reflect their regional and temporal characteristics: dry regime (DR), Eastern Mountain regime (EMR), Central–Eastern Mountain regime (CEMR), Central–Eastern Mountain and Sonoran-isolated regime (CEMSIR), Central–Eastern Mountain and Sonoran regime (CEMSR), and nondiurnal regime (NDR).
Composites constructed from the National Center for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) Reanalysis Project data show that regime occurrence is related to the north–south location of the 500-hPa geopotential height ridge axis of the Bermuda High and the east–west location of the 500-hPa monsoon boundary, a boundary between dry air to the west and moist air to the east. Consequently, precipitable water (PW) from 1200 UTC Phoenix soundings is the best parameter for discriminating the six regimes.

Higgins, W., D. Ahijevych, J. Amador, A. Barros, E. Berbery, E. Caetano, R. Carbone, P. Ciesielski, R. Cifelli, M. Cortez-Vazquez, A. Douglas, M. Douglas, G. Emmanuel, C. Fairall, D. Gochis, D. Gutzler, T. Jackson, R. Johnson, C. King, T. Lang, M. Lee, D. Lettenmaier, R. Lobato, V. Magaña, J. Meitin, K. Mo, S. Nesbitt, F. Ocampo-Torres, E. Pytlak, P. Rodgers, S. Rutledge, J. Schemm, S. Schubert, A. White, C. Williams, A. Wood, R. Zamora, C. Zhang, 2006: The NAME 2004 Field Campaign and Modeling Strategy. Bulletin of the American Meteorological Society, 87, 79-94.

Horgan, K. L., D. M. Schultz, R. H. Johns, S. F. Corfidi, J. E. Hales, 2006: A five-year climatology of elevated severe convective storms in the United States east of the Rocky Mountains. Preprints, Severe Local Storms Special Symposium, Atlanta, GA, USA, Amer. Meteor. Soc., CD-ROM, P1.22.

Available online at ://http://www.cimms.ou.edu/~schultz/papers/horganetal2006.pdf.

Horgan, K. L., D. M. Schultz, R. H. Johns, J. E. Hales, S. F. Corfidi, 2007: A five-year climatology of elevated severe convective storms in the United States east of the Rocky Mountains. Weather and Forecasting, 22, 1031-1044.

Kain, J. S., S. J. Weiss, J. J. Levit, M. E. Baldwin, D. R. Bright, 2006: Examination of convection-allowing configurations of the WRF model for the prediction of severe convective weather: The SPC/NSSL Spring Program 2004. Weather and Forecasting, 21, 167-181.

Convection-allowing configurations of the Weather Research and Forecast (WRF) model were evaluated during the 2004 Storm Prediction Center–National Severe Storms Laboratory Spring Program in a simulated severe weather forecasting environment. The utility of the WRF forecasts was assessed in two different ways. First, WRF output was used in the preparation of daily experimental human forecasts for severe weather. These forecasts were compared with corresponding predictions made without access to WRF data to provide a measure of the impact of the experimental data on the human decision-making process. Second, WRF output was compared directly with output from current operational forecast models. Results indicate that human forecasts showed a small, but measurable, improvement when forecasters had access to the high-resolution WRF output and, in the mean, the WRF output received higher ratings than the operational Eta Model on subjective performance measures related to convective initiation, evolution, and mode. The results suggest that convection-allowing models have the potential to provide a value-added benefit to the traditional guidance package used by severe weather forecasters.

Kain, J. S., S. J. Weiss, D. R. Bright, M. E. Baldwin, J. J. Levit, G. W. Carbin, C. S. Schwartz, M. L. Weisman, K. K. Droegemeier, D. B. Weber, K. W. Thomas, 2007: Some practical considerations for the first generation of operational convection-allowing NWP: How much resolution is enough?. Preprints, 22th Conference on Weather Analysis and Forecasting/18th Conference on Numerical Weather Prediction, Park City, UT, USA, Amer. Meteor. Soc., CD-ROM, 3B.5.

Kanak, K. M., J. M. Straka, D. M. Schultz, 2006: Simulations of mammatus-like clouds and comparison with observations, cloud based detrainment instability theory and Scorer's conjectures.. Preprints, 12th Conf. Cloud Physics, Madison, WI, USA, Amer. Meteor. Soc., CD-ROM, P1.57.

Available online at ://http://ams.confex.com/ams/Madison2006/techprogram/paper_112359.htm.

Killeen, T. J., M. Douglas, T. Consiglio, P. M. Jorgensen, J. Mejia, 2007: Dry spots and wet spots in the Andean hotspot. Journal of Biogeography, 34, .

Kong, F., M. XUE, D. R. Bright, M. C. Coniglio, K. W. Thomas, Y. Wang, D. Weber, J. S. Kain, S. J. Weiss, J. Du, 2007: Preliminary analysis on the real-time storm-scale ensemble forecasts produced as a part of the NOAA Hazardous Weather Testbed 2007 Spring Experiment.. Preprints, Preprints, 22th Conference on Weather Analysis and Forecasting/18th Conference on Numerical Weather Prediction, Park City, UT, USA, Amer. Meteor. Soc, CD-ROM, 3B.2.

Kunkel, K. E., P. Bromirski, H. E. Brooks, T. Cavazos, A. V. Douglas, D. R. Easterling, K. A. Emanuel, P. Y. Groisman, G. J. Holland, T. R. Knutson, J. P. Kossin, P. D. Komar, D. H. Levinson, R. L. Smith, J. Allan, R. Assel, S. Changnon, J. Lawrimore, K. B. Liu, T. Peterson, 2008: Observed Changes in Weather and Climate Extremes. Weather and Climate Extremes in a Changing Climate. Regions of Focus: North America, Hawaii, Caribbean, and U.S. Pacific Islands. Synthesis and Assessment Product 3.3 Report by the U.S. Climate Change Science Program and the Subcommittee on Global Change, T. M. Karl, G. A. Meehl, C. D. Miller, S. J. Hassol, A. M. Waple, W. L. Murray, Ed(s)., U.S. Climate Change Science Program and the Subcommittee on Glob, 35-80.

Lengyel, M. M., H. E. Brooks, R. L. Holle, M. A. Cooper, 2005: Lightning casualties and their proximity to surrounding cloud-to-ground lightning. Preprints, 14th Symposium on Education, San Diego, CA, USA, American Meteorological Society, CD-ROM, P1.35.

Lewis, J., R. Maddox, C. Crisp, 2006: Architect of sever storms forecasting: Colonel Robert C. Miller. Bulletin of the American Meteorological Society, 87, .

Liang, X. Z., M. XU, K. E. Kunkel, G. A. Grell, J. S. Kain, 2007: Regional Climate Model Simulation of U.S.–Mexico Summer Precipitation Using the Optimal Ensemble of Two Cumulus Parameterizations. Journal of Climate, 20, 5201-5207.

Marchand, R. N., N. Beagley, S. Thompson, T. P. Ackerman, D. M. Schultz, 2006: A bootstrap technique for testing the relationship between local-scale radar observations of cloud occurrence and large-scale atmospheric fields. Journal of the Atmospheric Sciences, 63, 2813-2830.

Marsh, P. T., H. E. Brooks, D. J. Karoly, 2007: Assessment of the severe weather environment in North America simulated by a global climate model. Atmospheric Science Letters, 8, 106.

Annual and seasonal cycles of convectively important atmospheric parameters for North America have been computed using the Community Climate System Model version 3 (CCSM3) Global Climate Model using a decade of CCSM3 data. Results for the spatial and temporal distributions of environments conducive to severe convective weather qualitatively agree with observational estimates from NCAR/NCEP global reanalyses, although the model underestimates the frequency of occurrence of severe weather environments. This result demonstrates the possibility for future studies aimed at determining possible changes in the distribution of severe weather environments associated with global climate change.

Mejia, J. F., M. Douglas, 2005: Mean structure and variability of the low-level jet across the central Gulf of California from NOAA WP-3D flight level observations during the North American Monsoon Experiment. Preprints, 6th Conference on Coastal Atmospheric and Oceanic Prediction and Processes (6COASTAL), San Diego, CA, USA, American Meteorological Society, CD-ROM, 5.8.

Morss, R. E., J. K. Lazo, B. G. Brown, H. E. Brooks, P. T. Ganderton, B. N. Mills, 2008: Societal and Economic Research and Applications For Weather Forecasts: Priorities for the North American THORPEX Program. Bulletin of the American Meteorological Society, 89, 335-346.

Despite the meteorological community's long-term interest in weather–society interactions, efforts to understand socioeconomic aspects of weather prediction and to incorporate this knowledge into the weather prediction system have yet to reach critical mass. This article aims to reinvigorate interest in societal and economic research and applications (SERA) activities within the meteorological and social science communities by exploring key SERA issues and proposing SERA priorities for the next decade.

The priorities were developed by the authors, building on previous work, with input from a diverse group of social scientists and meteorologists who participated in a SERA workshop in August 2006. The workshop was organized to provide input to the North American regional component of THORPEX: A Global Atmospheric Research Programme, but the priorities identified are broadly applicable to all weather forecast research and applications.

To motivate and frame SERA activities, we first discuss the concept of high-impact weather forecasts and the chain from forecast creation to value realization. Next, we present five interconnected SERA priority themes—use of forecast information in decision making, communication of forecast uncertainty, user-relevant verification, economic value of forecasts, and decision support—and propose research integrated across the themes.

SERA activities can significantly improve understanding of weather–society interactions to the benefit of the meteorological community and society. However, reaching this potential will require dedicated effort to bring together and maintain a sustainable interdisciplinary community.

Schultz, D. M., 2005: A review of cold fronts with prefrontal troughs and wind shifts. Monthly Weather Review, 133, 2449-2472.

Schultz, D. M., K. M. Kanak, J. M. Straka, R. J. Trapp, B. A. Gordon, D. S. Zrnic, G. H. Bryan, A. J. Durant, T. J. Garrett, P. M. Klein, D. K. Lilly, 2006: The mysteries of mammatus clouds: Observations and formation mechanisms. Journal of the Atmospheric Sciences, 63, 2409-2435.

Mammatus clouds are an intriguing enigma of atmospheric fluid dynamics and cloud physics. Most commonly observed on the underside of cumulonimbus anvils, mammatus also occur on the underside of cirrus, cirrocumulus, altocumulus, altostratus, and stratocumulus, as well as in contrails from jet aircraft and pyrocumulus ash clouds from volcanic eruptions. Despite their aesthetic appearance, mammatus have been the sub ject of few quantitative research studies. Observations of mammatus have been obtained largely through serendipitous opportunities with a single observ- ing system (e.g., aircraft penetrations, visual observations, lidar, radar) or tangential observations from field programs with other ob jectives. Theories describing mammatus remain untested as ad- equate measurements for validation do not exist because of the small distance scales and short time scales of mammatus. Modeling studies of mammatus are virtually nonexistent. As a result, relatively little is known about the environment, formation mechanisms, properties, microphysics, and dynamics of mammatus.

This paper presents a review of mammatus clouds that addresses these mysteries. Previous observations of mammatus and proposed formation mechanisms are discussed. These hypothesized mechanisms are anvil subsidence, subcloud evaporation/sublimation, melting, hydrometeor fallout, cloud-base detrainment instability, radiative effects, gravity waves, Kelvin-Helmholtz instability, Rayleigh-Taylor instability, and Rayleigh-Bénard-like convection. Other issues addressed in this paper include whether mammatus are composed of ice or liquid water hydrometeors, why mammatus are smooth, what controls the temporal and spatial scales and organization of individual mammatus lobes, and what are the properties of volcanic ash clouds that produce mammatus? The similarities and differences between mammatus, virga, stalactites, and reticular clouds are also discussed. Finally, because much still remains to be learned, research opportunities are described for using mammatus as a window into the microphysical, turbulent, and dynamical processes occurring on the underside of clouds.

Schultz, D. M., 2006: Comments on "Cloud-resolving model simulations of multiply-banded frontal clouds" by Pizzamei et al. (2005). Quarterly Journal of the Royal Meteorological Society, 132, 2095-2096.

Schultz, D. M., K. Seitter, L. Bosart, C. Gorski, C. Iovinella, 2007: Factors affecting the increasing costs of AMS conferences. Bulletin of the American Meteorological Society, 88, 408-417.

Schultz, D. M., C. C. Weiss, P. M. Hoffman, 2007: The synoptic regulation of dryline intensity. Monthly Weather Review, 135, 1699-1709.

Schultz, D. M., 2007: Banded convection caused by frontogenesis in a conditionally, symmetrically, and inertially unstable environment. Monthly Weather Review, 135, 2095-2110.

Several east–west-oriented bands of clouds and light rain formed on 20 July 2005 over eastern Montana and the Dakotas. The cloud bands were spaced about 150 km apart, and the most intense band was about 20 km wide and 300 km long, featuring areas of maximum radar reflectivity factor of about 50 dBZ. The cloud bands formed poleward of an area of lower-tropospheric frontogenesis, where air of modest convective available potential energy was being lifted. During initiation and maintenance of the bands, mesoscale regions of dry symmetric and inertial instability were present in the region of the bands, suggesting a possible mechanism for the banding. Interpretation of the extant instabilities in the region of the bands was sensitive to the methodology to assess the instability. The release of these instabilities produced circulations with enough vertical motion to lift parcels to their lifting condensation level, resulting in the observed cloud bands. A high-resolution, numerical weather prediction model demonstrated that forecasting these types of events in such real-time models is possible, although the timing, evolution, and spacing of the bands were not faithfully reproduced. This case is compared to two previous cases in the literature where banded convection was associated with a combination of conditional, symmetric, and inertial instability.

Schultz, D. M., R. M. Friedman, 2007: Tor Harold Percival Bergeron. New Dictionary of Scientific Biography, N. Koertge, Ed(s)., Charles Scribner's Sons, 245-250.

Schultz, D. M., F. Zhang, 2007: Baroclinic development within zonally varying flows. Quarterly Journal of the Royal Meteorological Society, 133, 1101-1112.

Schultz, D. M., J. A. Knox, 2007: Banded convection caused by frontogenesis in a conditionally, symmetrically and inertially unstable environment. Monthly Weather Review, 135, 2095-2110.

Sears-Collins, A. L., D. M. Schultz, R. H. Johns, 2006: The spatial and temporal variability of drizzle in the United States and Canada.. Weather and Forecasting, 19, 3629-3639.

A climatology of nonfreezing drizzle is created using surface observations from 584 stations across the United States and Canada over the 15 years 1976 - 1990. Drizzle falls 50 - 200 h a year in most locations in the eastern United States and Canada, whereas drizzle falls less than 50 h a year in the west, except for coastal Alaska and several western basins. The eastern and western halves of North America are separated by a strong gradient in drizzle frequency along roughly 100° W, as large as about an hour a year over 2 km. Forty percent of the stations have a drizzle maximum from November to January, whereas only 13% of stations have a drizzle maximum from June to August. Drizzle occurrence exhibits a seasonal migration from eastern Canada and the central portion of the Northwest Territories in summer, equatorward to most of the eastern United States and southeast Canada in early winter, to southeastern Texas and the eastern United States in late winter, and back north to eastern Canada in the spring. The diurnal hourly frequency of drizzle across the United States and Canada increases sharply from 0900 UTC to 1200 UTC, followed by a steady decline from 1300 UTC to 2300 UTC. Diurnal drizzle frequency is maximum in the early morning, in agreement with other studies. Drizzle occurs during a wide range of atmospheric conditions at the surface. Drizzle has occurred at sea level pressures below 960 hPa and above 1040 hPa. Most drizzle, however, occurs at higher than normal sea level pressure, with more than 64% occurring at a sea level pressure of 1015 hPa or higher. A third of all drizzle falls when the winds are from the northeast quadrant (360° - 89°), suggesting that continental drizzle events tend to be found poleward of surface warm fronts and equatorward of cold-sector surface anticyclones. Two-thirds of all drizzle occurs with wind speeds 2.0 - 6.9 m s-1, with 7.6% in calm wind and 5% at wind speeds greater than or equal to 10 m s-1. Most drizzle (61%) occurs with visibilities between 1.5 and 5.0 km, with only about 20% occurring at visibilities less than 1.5 km.

Stensrud, D. J., H. E. Brooks, 2005: The future of peer review?. Weather and Forecasting, 20, 825-826.

No abstract.

Stensrud, D. J., N. Yussouf, M. E. Baldwin, J. T. McQueen, J. Du, B. Zhou, B. Ferrier, G. Manikin, F. M. Ralph, J. M. Wilczak, A. B. White, I. Djlalova, J. W. Bao, R. J. Zamora, S. G. Benjamin, P. A. Miller, T. L. Smith, T. Smirnova, M. F. Barth, 2006: The New England High-Resolution Temperature Program. Bulletin of the American Meteorological Society, 87, 491-498.

The New England High-Resolution Temperature Program seeks to improve the accuracy of summertime 2-m temperature and dewpoint temperature forecasts in the New England region through a collaborative effort between the research and operational components of the National Oceanic and Atmospheric Administration (NOAA). The four main components of this program are 1) improved surface and boundary layer observations for model initialization, 2) special observations for the assessment and improvement of model physical process parameterization schemes, 3) using model forecast ensemble data to improve upon the operational forecasts for near surface variables, and 4) transfering knowledge gained to commercial weather services and end users. Since 2002 this program has enhanced surface temperature observations by adding 70 new automated Cooperative Observer Program (COOP) sites, identified and collected data from over 1000 non-NOAA mesonet sites, and deployed boundary layer profilers and other special instrumentation throughout the New England region to better observe the surface energy budget. Comparisons of these special data sets with numerical model forecasts indicate that near surface temperature errors are strongly correlated to errors in the model predicted radiation fields. The attenuation of solar radiation by aerosols is one potential source of the model radiation bias. However, even with these model errors, results from bias-corrected ensemble forecasts are more accurate than the operational model output statistics (MOS) forecasts for 2-m temperature and dewpoint temperature, while also providing reliable forecast probabilities. Discussions with commerical weather vendors and end users have emphasized the potential economic value of these probabilistic ensemble-generated forecasts.

Stuart, N. A., P. S. Market, B. Telfeyan, G. M. Lackmann, K. Carey, H. E. Brooks, B. C. Motta, K. Reeves, 2006: The future of humans in an increasingly automated forecast process. Bulletin of the American Meteorological Society, 87, 1-6.

The meteorological community is considering new roles for forecasters as increased accuracy in computer-generated weather forecasts continues to reduce the need for human intervention.

Available online at ://http://www.nssl.noaa.gov/users/brooks/public_html/papers/stuart.pdf.

Trapp, R. J., S. A. Tessendorf, E. S. Godfrey, H. E. Brooks, 2005: Tornadoes from Squall Lines and Bow Echoes. Part I: Climatological Distribution. Weather and Forecasting, 20, 23-34.

The primary objective of this study was to estimate the percentage of U.S. tornadoes that are spawned annually by squall lines and bow echoes, or quasi-linear convective systems (QLCSs). This was achieved by examining radar reflectivity images for every tornado event recorded during 1998-2000 in the contiguous United States. Based on these images, the type of storm associated with each tornado was classified as cell, QLCS, or other. Of the 3828 tornadoes in the database, 79% were produced by cells, 18% were produced by QLCSs, and the remaining 3% were produced by other storm types, primarily rainbands of landfallen tropical cyclones. Geographically, these percentages as well as those based on tornado days exhibited wide variations. For example, 50% of the tornado days in Indiana were associated with QLCSs. In an examination of other tornado attributes, statistically more weak (F1) and fewer strong (F2-F3) tornadoes were associated with QLCSs than with cells. QLCS tornadoes were more probable during the winter months than were cells. And finally, QLCS tornadoes displayed a comparatively higher and statistically significant tendency to occur during the late night/early morning hours. Further analysis revealed a disproportional decrease in F0-F1 events during this time of day, which led the authors to propose that many (perhaps as many as 12% of the total) weak QLCSs tornadoes were not reported.

Trapp, R. J., N. S. Diffenbaugh, H. E. Brooks, M. E. Baldwin, E. D. Robinson, J. S. Pal, 2007: Changes in severe thunderstorm environment frequency during the 21st century caused by anthropogenically enhanced global radiative forcing. Proceedings of the National Academy of Sciences of the United States of America, 104, 19723.

Severe thunderstorms comprise an extreme class of deep convective clouds and produce high-impact weather such as destructive surface winds, hail, and tornadoes. This study addresses the question of how severe thunderstorm frequency in the United States might change because of enhanced global radiative forcing associated with elevated greenhouse gas concentrations. We use global climate models and a high-resolution regional climate model to examine the larger-scale (or "environmental") meteorological conditions that foster severe thunderstorm formation. Across this model suite, we find a net increase during the late 21st century in the number of days in which these severe thunderstorm environmental conditions (NDSEV) occur. Attributed primarily to increases in atmospheric water vapor within the planetary boundary layer, the largest increases in NDSEV are shown during the summer season, in proximity to the Gulf of Mexico and Atlantic coastal regions. For example, this analysis suggests a future increase in NDSEV of 100% or more in locations such as Atlanta, GA, and New York, NY. Any direct application of these results to the frequency of actual storms also must consider the storm initiation.

Van Den Broeke, M. S., D. M. Schultz, R. H. Johns, J. S. Evans, J. E. Hales, 2005: Cloud-to-ground lightning production in strongly forced, low-instability convective lines associated with damaging wind. Weather and Forecasting, 20, 517-530.

Vasiloff, S. V., D. J. Seo, K. W. Howard, J. Zhang, D. H. Kitzmiller, M. G. Mullusky, W. F. Krajewski, E. A. Brandes, R. M. Rabin, D. S. Berkowitz, H. E. Brooks, J. A. McGinley, R. J. Kuligowski, B. G. Brown, 2007: Improving QPE and Very Short Term QPF: An Initiative for a Community-Wide Integrated Approach. Bulletin of the American Meteorological Society, 88, 1899-1911.

Accurate quantitative precipitation estimates (QPE) and very short term quantitative precipitation forecasts (VSTQPF) are critical to accurate monitoring and prediction of water-related hazards and water resources. While tremendous progress has been made in the last quarter-century in many areas of QPE and VSTQPF, significant gaps continue to exist in both knowledge and capabilities that are necessary to produce accurate high-resolution precipitation estimates at the national scale for a wide spectrum of users. Toward this goal, a national next-generation QPE and VSTQPF (Q2) workshop was held in Norman, Oklahoma, on 28–30 June 2005. Scientists, operational forecasters, water managers, and stakeholders from public and private sectors, including academia, presented and discussed a broad range of precipitation and forecasting topics and issues, and developed a list of science focus areas. To meet the nation's needs for the precipitation information effectively, the authors herein propose a community-wide integrated approach for precipitation information that fully capitalizes on recent advances in science and technology, and leverages the wide range of expertise and experience that exists in the research and operational communities. The concepts and recommendations from the workshop form the Q2 science plan and a suggested path to operations. Implementation of these concepts is expected to improve river forecasts and flood and flash flood watches and warnings, and to enhance various hydrologic and hydrometeorological services for a wide range of users and customers. In support of this initiative, the National Mosaic and Q2 (NMQ) system is being developed at the National Severe Storms Laboratory to serve as a community test bed for QPE and VSTQPF research and to facilitate the transition to operations of research applications. The NMQ system provides a real-time, around-the-clock data infusion and applications development and evaluation environment, and thus offers a community-wide platform for development and testing of advances in the focus areas.

Vera, C., J. Beaz, M. Douglas, C. Emmanuel, J. Marengo, J. Meitin, M. Nicolini, J. Nouges-Paegle, J. Paegle, O. Penalba, P. Salio, C. Saulo, M. A. Silva-Dias, P. Silva-Dias, E. Zipser, 2006: The South American Low-Level Jet Experiment. Bulletin of the American Meteorological Society, 87, 63-77.

Verbout, S. M., L. M. Leslie, H. E. Brooks, D. Schultz, D. Karoly, 2005: Tornado outbreaks associated with land-falling tropical cyclones in the Atlantic Basin. Preprints, 6th Conference on Coastal Atmospheric and Oceanic Prediction and Processes, San Diego, CA, USA, American Meteorological Society, CD-ROM, 7.1.

Available online at ://http://ams.confex.com/ams/Annual2005/techprogram/paper_84926.htm.

Verbout, S. M., H. E. Brooks, L. M. Leslie, D. M. Schultz, 2006: Evolution of the U.S. tornado database: 1954-2004.. Weather and Forecasting, 21, 86-93.

Over the last 50 yr, the number of tornadoes reported in the United States has doubled from about 600 per year in the 1950s to around 1200 in the 2000s. This doubling is likely not related to meteorological causes alone. To account for this increase a simple least squares linear regression was fitted to the annual number of tornado reports. A "big tornado day" is a single day when numerous tornadoes and/or many tornadoes exceeding a specified intensity threshold were reported anywhere in the country. By defining a big tornado day without considering the spatial distribution of the tornadoes, a big tornado day differs from previous definitions of outbreaks. To address the increase in the number of reports, the number of reports is compared to the expected number of reports in a year based on linear regression. In addition, the F1 and greater Fujita-scale record was used in determining a big tornado day because the F1 and greater series was more stationary over time as opposed to the F2 and greater series. Thresholds were applied to the data to determine the number and intensities of the tornadoes needed to be considered a big tornado day. Possible threshold values included fractions of the annual expected value associated with the linear regression and fixed numbers for the intensity criterion. Threshold values of 1.5% of the expected annual total number of tornadoes and/or at least 8 F1 and greater tornadoes identified about 18.1 big tornado days per year. Higher thresholds such as 2.5% and/or at least 15 F1 and greater tornadoes showed similar characteristics, yet identified approximately 6.2 big tornado days per year. Finally, probability distribution curves generated using kernel density estimation revealed that big tornado days were more likely to occur slightly earlier in the year and have a narrower distribution than any given tornado day.

Available online at ://http://www.cimms.ou.edu/~schultz/pubs/verboutetal06.pdf.

Verbout, S. M., D. M. Schultz, L. M. Leslie, H. E. Brooks, D. J. Karoly, K. L. Elmore, 2007: Tornado outbreaks associated with landfalling hurricanes in the north Atlantic Basin: 1954–2004. Meteorology and Atmospheric Physics, 97, 255-271.

Tornadoes are a notable potential hazard associated with landfalling hurricanes. The purpose of this paper is to discriminate hurricanes that produce numerous tornadoes (tornado outbreaks) from those that do not (nonoutbreaks). The data consists of all hurricane landfalls that affected the United States from the North Atlantic basin from 1954 to 2004 and the United States tornado record over the same period. Because of the more than twofold increase in the number of reported tornadoes over these 51 years, a simple least-squares linear regression ("the expected number of tornadoes") was fit to the annual number of tornado reports to represent a baseline for comparison.

The hurricanes were sorted into three categories. The first category, outbreak hurricanes, was determined by hurricanes associated with the number of tornado reports exceeding a threshold of 1.5% of the annual expected number of tornadoes and at least 8 F1 and greater tornadoes during the time of landfall (from outer rainbands reaching shore to dissipation of the system). Eighteen hurricane landfalls were classified as outbreak hurricanes. Second, 37 hurricanes having less han 0.5% of the annual expected number of tornadoes were classified as nonoutbreak landfalls. Finally, 28 hurricanes that were neither outbreak nor nonoutbreak hurricanes were classified as midclass hurricane landfalls.

Stronger hurricanes are more likely to produce tornado outbreaks than weaker hurricanes. While 78% of outbreak hurricanes were category 2 or greater at landfall, only 32% of nonoutbreak hurricanes were category 2 or greater at landfall. Hurricanes that made landfall along the southern coast of the United States and recurved northeastward were more likely to produce tornadoes than those that made landfall along the east coast or those that made landfall along the southern coast but did not recurve. Recurvature was associated with a 500-hPa trough in the jet stream, which also contributed to increased deep-layer shear through the hurricane, favoring mesocyclogenesis, and increased the low-level shear, favoring tornadogenesis. The origin of the hurricane, date of landfall, and El Niño-Southern Oscillation phase do not appear to be factors in outbreak hurricane creation. The results of this study help clarify inconsistencies in the previous literature regarding tornado occurrences in landfalling hurricanes.

Available online at ://http://www.springerlink.com/content/8132257282886516/fulltext.pdf.

Wandishin, M. S., M. E. Baldwin, S. L. Mullen, J. V. Cortinas, 2005: Short-range ensemble forecasts of precipitation type. Weather and Forecasting, 20, 609-626.

Ware, E. C., D. M. Schultz, H. E. Brooks, P. J. Roebber, S. L. Bruening, 2006: Improving snowfall forecasting by accounting for the climatological variability of snow density.. Weather and Forecasting, 21, 94-103.

Accurately forecasting snowfall is a challenge. In particular, one poorly understood component of snowfall forecasting is determining the snow ratio. The snow ratio is the ratio of snowfall to liquid equivalent and is inversely proportional to the snow density. In a previous paper, an artificial neural network was developed to predict snow ratios probabilistically in three classes: heavy (1:1 < ratio < 9:1), average (9:1 <= ratio <= 15:1), and light (ratio > 15:1). A Web-based application for the probabilistic prediction of snow ratio in these three classes based on operational forecast model soundings and the neural network is now available. The goal of this paper is to explore the statistical characteristics of the snow ratio to determine how temperature, liquid equivalent, and wind speed can be used to provide additional guidance (quantitative, wherever possible) for forecasting snowfall, especially for extreme values of snow ratio. Snow ratio tends to increase as the low-level (surface to roughly 850 mb) temperature decreases. For example, mean low-level temperatures greater than −2.7°C rarely (less than 5% of the time) produce snow ratios greater than 25:1, whereas mean low-level temperatures less than −10.1°C rarely produce snow ratios less than 10:1. Snow ratio tends to increase strongly as the liquid equivalent decreases, leading to a nomogram for probabilistic forecasting snowfall, given a forecasted value of liquid equivalent. For example, liquid equivalent amounts 2.8–4.1 mm (0.11–0.16 in.) rarely produce snow ratios less than 14:1, and liquid equivalent amounts greater than 11.2 mm (0.44 in.) rarely produce snow ratios greater than 26:1. The surface wind speed plays a minor role by decreasing snow ratio with increasing wind speed. Although previous research has shown simple relationships to determine the snow ratio are difficult to obtain, this note helps to clarify some situations where such relationships are possible.

Available online at ://http://www.cimms.ou.edu/~schultz/pubs/wareetal06.pdf.

Watts, C. J., R. L. Scott, J. Garatuza-Payan, J. C. Rodriguez, J. H. Prueger, W. P. Kustas, M. Douglas, 2007: Changes in Vegetation Condition and Surface Fluxes during NAME 2004. Journal of Climate, 20, .

Weiss, S., J. Kain, L. Wicker, R. Davies-Jones, D. Bright, J. Levit, G. Carbin, M. Baldwin, 2005: Evaluating the skill of daily explicit predictions of mesocyclones in multiple high-resolution WRF model forecasts during the 2005 SPC/NSSL Spring Program.. Preprints, 12th Conf. On Mesoscale Processes,, Albuquerque, NM, USA, Amer. Meteor. Soc., no preprint.

Weiss, C. C., D. M. Schultz, 2006: Synoptic and mesoscale influences on west Texas dryline development and associated convection.. Preprints, 23rd Conf. on Severe Local Storms, St. Louis, MO, USA, Amer. Meteor. Soc., CD-ROM, 2.6.

Available online at ://http://ams.confex.com/ams/23SLS/techprogram/paper_115462.htm.

Weiss, S. J., J. S. Kain, D. R. Bright, J. J. Levit, M. Pyle, Z. I. Janjic, B. Ferrier, J. Du, M. L. Weisman, M. Xue, 2007: The NOAA Hazardous Weather Testbed: Collaborative testing of ensemble and convection-allowing WRF models and subsequent transfer to operations at the Storm Prediction Center.. Preprints, 22th Conference on Weather Analysis and Forecasting/18th Conference on Numerical Weather Prediction, Park City, UT, USA, Amer. Meteor. Soc., CD-ROM, 6B.4.

Xue, M., F. Kong, D. Weber, K. W. Thomas, Y. Wang, K. Brewster, K. K. Droegemeier, J. S. Kain, S. J. Weiss, D. R. Bright, M. S. Wandishin, M. C. Coniglio, J. Du, 2007: CAPS realtime storm-scale ensemble and high-resolution forecasts as part of the NOAA Hazardous Weather Testbed 2007 Spring Experiment.. Preprints, 22th Conference on Weather Analysis and Forecasting/18th Conference on Numerical Weather Prediction, Park City, UT, USA, Amer. Meteor. Soc., CD-ROM, 3B.1.

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